Transforming Ideas Into Impact Through Intelligent Research
Analyzing User Emotions via Physiology Signals [Data Science and Pattern Recognition, 2017]
Explores how physiological signals such as heart rate and skin response can be analyzed using data-driven techniques to understand and classify user emotions — an early step toward emotion-aware intelligent systems.
A Simple Deep Q-Network Based Feature Selection Method [IEEE APWCS 2023]
Proposes a reinforcement learning approach using Deep Q-Networks for efficient feature selection, improving model performance while reducing computational cost.
Key Success Factor of Marketing Intelligence in Higher Education: Systematic Literature Review [IEEE ICIMTech 2023]
Analyzes critical factors influencing marketing intelligence success within higher education institutions, offering a structured synthesis of recent academic studies.
Accuracy-Time Efficient Hyperparameter Optimization Using Actor-Critic-Based Reinforcement Learning [IEEE IoTaIS 2022]
Introduces an actor-critic reinforcement learning approach to optimize machine learning hyperparameters effectively, balancing accuracy and training time.
Radar and Camera Fusion for Object Forecasting in Driving Scenarios [IEEE MCSoC 2022]
Develops a multi-sensor data fusion system integrating radar and camera inputs to improve prediction accuracy for autonomous driving applications.
Data Fusion Driven Lane-Level Precision Data Transmission for V2X Road Applications [IEEE MCSoC 2021]
Presents a precision data transmission framework leveraging data fusion techniques for vehicle-to-everything (V2X) communication systems.
A Neural Network-Based Multisensor Data Fusion Approach for Enabling Situational Awareness of Vehicles [IEEE ICPAI 2020]
Designs a neural network model that integrates multiple sensor inputs to enhance situational awareness and safety in smart vehicles.
A New Online Charging System Based on Context of Mobile Users [IEEE ICCE-TW 2019]
Proposes a context-aware online charging system that dynamically adapts to user behavior and environmental context to improve service efficiency.
AED: Adaptive Energy-Efficient Data Transmission Scheme for Heart Disease Detection [IEEE DASC/PiCom/DataCom/CyberSciTech 2017]
Introduces an adaptive and energy-efficient data transmission scheme tailored for wearable devices monitoring heart disease, balancing energy use with data accuracy.
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